I help teams figure out where AI fits in their stack — then I build it.
RAG pipelines, agent frameworks, LLM integrations. Strategy that doesn't stop at the whiteboard.
Production-ready system for querying large document collections. Multi-document retrieval with citation tracking. The kind of thing that actually needs to work at scale. | MCP server that gives LLMs direct access to GitHub — code search, issue management, repo analysis. Built on the protocol, not around it. |
Framework for coordinating specialized AI agents across complex workflows — communication protocols, task delegation, result aggregation, agent state via Redis. | AI-powered tool that breaks down code snippets into plain English. Supports multiple languages with detailed logic and pattern breakdowns. |
AI / ML
Backend
Infra
I write about AI strategy, LLM applications, and engineering at linkedin.com/in/sirematrix
AI adoption for engineering teams · RAG system design patterns · building reliable agent systems
